Is the Convergence of the Racial Wage Gap Illusory?

I demonstrate that the literature on the racial wage gap has systematically overstated the gains made by African American men by ignoring their withdrawal from the labor force. Three sources of selection-bias are identified: imposing sample selection criteria based on labor supply, trimming wages on the basis of real-dollar cutoffs, and making inferences based on Current Population Survey (CPS) data whose truncated sampling design excludes the growing incarcerated population. To recover the counterfactual distribution of skill-prices for non-workers, I implement a quasi-bounds estimator that does not require the use of arbitrary exclusion restrictions for identification and find that: (1) Corrected estimates of the racial wage gap indicate a substantial role for the efficacy of the Civil Rights Act and related initiatives in affecting convergence in segregated states; ignoring selection causes estimates of convergence in the South as well as the within-cohort component of this change to be understated. (2) In contrast to the sharp convergence observed in standard wage series from 1970-90, selectivity corrected estimates indicate complete stagnation over this period with a divergence of 3.5 to 6 percentage points between 1980 and 1990. Almost half of this divergence is missed through the exclusion of the incarcerated population. The selective withdrawal hypothesis can explain 85 percent of the observed convergence between 1970 and 1990 and 40 percent of the 1960-90 convergence. (3) The disproportionate presence of highly skilled blacks in the armed forces (who are also excluded from CPS analysis) causes estimates of the racial gap to be overstated by 1 to 2 percentage points. (4) The relative increase in non-participation is a supply-side effect driven more by a massive increase in reservation wages for blacks at the bottom of the skill distribution, than by falling offer wages. (5) The significant gains made by black men during the 1960s and 1970s occured almost exclusively in the bottom offer wage decile, where significant numbers of black men were pushed out of the lowest white wage decile into higher quintiles. These gains constitute the primary location of black economic progress in the latter half of the 20th century.

The Labor Market Effects of Rising Health Insurance Premiums

Since 2000, premiums for employer-provided health insurance have increased by 59 percent with little corresponding increase in the generosity of coverage. The effect of this increase in costs on wages and employment will depend on workers' valuation of the benefit, the elasticities of labor supply and demand, and institutional constraints on employers' ability to lower wages. Measuring these effects is difficult, however, without a source of exogenous variation in the cost of benefits. We use variation in medical malpractice payments driven by the recent "medical malpractice crisis" to identify the causal effect of rising health insurance premiums on wages, employment, and health insurance coverage. We estimate that a 10 percent increase in health insurance premiums reduces the aggregate probability of being employed by 1.6 percent and hours worked by 1 percent, and increases the likelihood that a worker is employed only part-time by 1.9 percent. For workers covered by employer provided health insurance, this increase in premiums results in an offsetting decrease in wages of 2.3 percent. Thus, rising health insurance premiums may both increase the ranks of the unemployed and place an increasing burden on workers through decreased wages for workers with employer health insurance and decreased hours for workers moved from full time jobs with benefits to part time jobs without.

Does disability explain state-level differences in the quality of Medicare beneficiary hospital inpatient care?

Almost 20 percent of the total U.S. population and 42 percent of the population over the age of sixty-six are disabled. Research has shown that the presence of a disability can crowd out treatment for medical conditions not necessarily related to the disability and that states that are disproportionately African-American have a lower quality of hospital care. This paper uses quality of care data from the Centers for Medicare and Medicaid Services (CMS) to determine whether disability also explains state-level differences in quality of hospital care. The quality of Medicare beneficiary hospital care was measured using process measures for several medical conditions, including acute myocardial infarction, heart failure, stroke, and pneumonia, that are the leading causes of mortality. We use nonlinear least squares to assess the association between Medicare beneficiary quality of care and state- and medical system–level characteristics. The result for the key variable of interest—disability—reveals that a 1 percent increase in a state's disability rate leads to a 1 percentage point reduction in the score of the state's quality of hospital care. Without explicitly incorporating strategies to eliminate disparities in care incurred by people with disabilities, CMS may not adequately promote the goal of delivering the highest quality of care to all Medicare beneficiaries.

Geography and Racial Health Disparities

An extensive literature has documented racial, ethnic, and socioeconomic disparities in health care and health outcomes. We argue that the influence of geography in medical practice needs to be taken seriously for both the statistical measurement of racial disparities, and in designing reforms to reduce disparities. Past research has called attention to disparities that occur within hospitals or provider groups; for example black patients who are treated differently from whites within a hospital. We focus on a different mechanism for disparities; African-Americans tend to live in areas or seek care in regions where quality levels for all patients, black and white, are lower. Thus ensuring equal access to health care at the local or hospital level may not by itself erase overall health care disparities. However, reducing geographic disparities in both the quality of care, and the quality of health care decisions by patients, could have a first-order impact on improving racial disparities in health care and health outcomes.

The Impact of Medical Liability Standards on Regional Variations in Physician Behavior: Evidence from the Adoption of National-Standard Rules

I explore the association between regional variations in physician behavior and the geographical scope of malpractice standards of care. I estimate a 30–50 percent reduction in the gap between state and national utilization rates of various treatments and diagnostic procedures following the adoption of a rule requiring physicians to follow national, as opposed to local, standards. These findings suggest that standardization in malpractice law may lead to greater standardization in practices and, more generally, that physicians may indeed adhere to specific liability standards. In connection with the estimated convergence in practices, I observe no associated changes in patient health

Outcomes Assessment and Health Care Reform

Argues for the use of outcomes assessment in measuring cost-effectiveness and quality to capture the overall impact of multi-dimensional treatment strategies and to identify healthcare systems that both adopt appropriate technologies and perform well

Testing a Roy Model with Productivity Spillovers: Evidence from the Treatment of Heart Attacks

Productivity spillovers are often cited as a reason for geographic specialization in production. A large literature in medicine documents specialization across areas in the use of surgical treatments, which is unrelated to patient outcomes. We show that a simple Roy model of patient treatment choice with productivity spillovers can generate these facts. Our model predicts that high-use areas will have higher returns to surgery, better outcomes among patients most appropriate for surgery, and worse outcomes among patients least appropriate for surgery. We find strong empirical support for these and other predictions of the model, and decisively reject alternative explanations commonly proposed to explain geographic variation in medical care.